Spark ⏩ How to handle fault tolerance? 🥺

In this tutorial, you will learn "What is fault tolerance and how does Spark handle it?"

Apache Spark handles fault tolerance through its resilient distributed dataset (RDD) abstraction and the use of lineage information to recover lost data. Here are the key mechanisms Spark uses for fault tolerance:

⏩Resilient Distributed Datasets (RDDs): Apache Spark handles fault tolerance through its resilient distributed dataset (RDD) abstraction

⏩RDD Lineage (Directed Acyclic Graph - DAG): Use of lineage information to recover lost data

⏩Immutable Data Structures: RDDs in Spark are immutable, meaning they cannot be modified in place. Instead, transformations on RDDs create new RDDs.

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